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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationTue, 20 Oct 2009 10:56:22 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/20/t1256057819xsh8s5rfymm5z2o.htm/, Retrieved Thu, 02 May 2024 16:28:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=48819, Retrieved Thu, 02 May 2024 16:28:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
- RMPD        [Harrell-Davis Quantiles] [] [2009-10-20 16:56:22] [244731fa3e7e6c85774b8c0902c58f85] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
345,0561798
413,1707317
348,9473684
414,2857143
356,1728395
396,9879518
460
408,3544304
506,7948718
476,25
338,4705882
408,7209302
436,2352941
431,25
430,7692308
513,75
534,7560976
449,2771084
525,4878049
432,8395062
461,25
501,4102564
378,4615385
431,6883117
449,6052632
460,2631579
364,4736842
372,6923077
397,375
376,75
440,8860759
391,6883117
353,6486486
512,173913
425,2238806
481,3846154
402,8125
541,1940299
413,6764706
375,5072464
418,8405797
502,8358209
457,1875
486,4516129
487,7966102
524,2622951
382,0895522
378,3823529
472,8787879
415,3125
448,28125
459,1044776
305,3521127
329,7183099
372,4637681
410,3125
415
459,3333333

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48819&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=48819&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48819&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01310.61804815885620.9581601859364
0.02318.19199740320117.0253393910196
0.03325.89163532038313.6066050711331
0.04332.53201937821511.2951840456643
0.05337.8961608558969.97562348311745
0.06342.2349834516479.33890971330733
0.07345.8877196443579.14769532201808
0.08349.1240091439599.24048831369394
0.09352.1175854838799.48191109637058
0.1354.9648639896089.74730787988732
0.11357.7087281788489.93094690446412
0.12360.3578444253049.96351749927225
0.13362.9019341407279.81971693219385
0.14365.3242591161829.51999444690247
0.15367.6113980475219.12167677581195
0.16369.7597800946268.7046004148612
0.17371.7786251894128.35480009387524
0.18373.6895017620018.14642309151032
0.19375.5232570739798.12690722613955
0.2377.3153936240938.30683766693104
0.21379.1010110724598.66139592438748
0.22380.9102613605289.1402747963431
0.23382.7649692237809.67961847403066
0.24384.6767416959710.2164305136047
0.25386.64659444692110.6923788037559
0.26388.6658972347411.0625764847387
0.27390.71829932340611.2949383793117
0.28392.78223625950911.3750443069269
0.29394.83362954345311.2995684941529
0.3396.8484518878511.0809417879458
0.31398.80492132146610.7390065178731
0.32400.68518598621410.3014620668767
0.33402.4764502340379.80013816241935
0.34404.1715598917719.26825217292529
0.35405.7691060375018.73960401156921
0.36407.2731247983868.24508007653534
0.37408.6924726349447.81423150204535
0.38410.0399511208967.46987309167804
0.39411.3312500569767.23117721981285
0.4412.5837774721767.10735667092814
0.41413.8154503567547.09913972063555
0.42415.0435279828257.19814143477923
0.43416.2835752873367.38746701697
0.44417.5486414457917.64382438323201
0.45418.848724275587.94237127691744
0.46420.1905631693768.25912420772818
0.47421.577764191098.5729620100899
0.48423.0112165390988.86810044642123
0.49424.4897179084769.13548223610172
0.5426.0106960081939.37094831390365
0.51427.5709016753349.57666521659115
0.52429.1669593038239.75773638577022
0.53430.7956917553869.92031451274067
0.54432.45418407493010.0687896915301
0.55434.13960428175710.2052496700981
0.56435.84884987863710.3264893388633
0.57437.57812597860610.4252763471060
0.58439.32257840930510.4911493615779
0.59441.07610017781810.5125768025280
0.6442.8314038000510.4798757235208
0.61444.5804100816810.3855025117221
0.62446.31495275125410.2289319472962
0.63448.02774510793310.0156459896998
0.64449.7135062113549.75939105853806
0.65451.3701058476189.48130411459812
0.66452.9995645402449.20928015849035
0.67454.6087417119838.97640750954777
0.68456.2095654792778.81847042184049
0.69457.8187034341518.7670271731395
0.7459.4566435497678.84699094476024
0.71461.1462410351299.06896312271629
0.72462.9108772344399.42705730804327
0.73464.772451985759.89927077380976
0.74466.74947124576710.4519240243500
0.75468.85548185799111.0430111824078
0.76471.09804098251411.6311000592799
0.77473.47830091943212.1774905188954
0.78475.99116911333212.6514921314529
0.79478.62590623406913.0294346277291
0.8481.36698808006613.2951826356831
0.81484.19509741269613.4381457257573
0.82487.08821686434213.4506612067782
0.83490.02291685570713.3279540938580
0.84492.97600267802913.0701671961552
0.85495.92663451714412.6859607803199
0.86498.85883388055112.1969489542557
0.87501.76398549343711.6398030143079
0.88504.64267512136411.0640725492933
0.89507.50517976328810.5217369380242
0.9510.37032739351710.0522921324418
0.91513.2632448558569.66689834304157
0.92516.2132974540999.34391521394727
0.93519.2534386472679.04649025258257
0.94522.4202138958958.75294136957157
0.95525.7492077668718.4688760098436
0.96529.2545355550188.18114065461974
0.97532.8772811142617.7992522905667
0.98536.3993723919487.23844630046968
0.99539.3705686407756.648348786937

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 310.618048158856 & 20.9581601859364 \tabularnewline
0.02 & 318.191997403201 & 17.0253393910196 \tabularnewline
0.03 & 325.891635320383 & 13.6066050711331 \tabularnewline
0.04 & 332.532019378215 & 11.2951840456643 \tabularnewline
0.05 & 337.896160855896 & 9.97562348311745 \tabularnewline
0.06 & 342.234983451647 & 9.33890971330733 \tabularnewline
0.07 & 345.887719644357 & 9.14769532201808 \tabularnewline
0.08 & 349.124009143959 & 9.24048831369394 \tabularnewline
0.09 & 352.117585483879 & 9.48191109637058 \tabularnewline
0.1 & 354.964863989608 & 9.74730787988732 \tabularnewline
0.11 & 357.708728178848 & 9.93094690446412 \tabularnewline
0.12 & 360.357844425304 & 9.96351749927225 \tabularnewline
0.13 & 362.901934140727 & 9.81971693219385 \tabularnewline
0.14 & 365.324259116182 & 9.51999444690247 \tabularnewline
0.15 & 367.611398047521 & 9.12167677581195 \tabularnewline
0.16 & 369.759780094626 & 8.7046004148612 \tabularnewline
0.17 & 371.778625189412 & 8.35480009387524 \tabularnewline
0.18 & 373.689501762001 & 8.14642309151032 \tabularnewline
0.19 & 375.523257073979 & 8.12690722613955 \tabularnewline
0.2 & 377.315393624093 & 8.30683766693104 \tabularnewline
0.21 & 379.101011072459 & 8.66139592438748 \tabularnewline
0.22 & 380.910261360528 & 9.1402747963431 \tabularnewline
0.23 & 382.764969223780 & 9.67961847403066 \tabularnewline
0.24 & 384.67674169597 & 10.2164305136047 \tabularnewline
0.25 & 386.646594446921 & 10.6923788037559 \tabularnewline
0.26 & 388.66589723474 & 11.0625764847387 \tabularnewline
0.27 & 390.718299323406 & 11.2949383793117 \tabularnewline
0.28 & 392.782236259509 & 11.3750443069269 \tabularnewline
0.29 & 394.833629543453 & 11.2995684941529 \tabularnewline
0.3 & 396.84845188785 & 11.0809417879458 \tabularnewline
0.31 & 398.804921321466 & 10.7390065178731 \tabularnewline
0.32 & 400.685185986214 & 10.3014620668767 \tabularnewline
0.33 & 402.476450234037 & 9.80013816241935 \tabularnewline
0.34 & 404.171559891771 & 9.26825217292529 \tabularnewline
0.35 & 405.769106037501 & 8.73960401156921 \tabularnewline
0.36 & 407.273124798386 & 8.24508007653534 \tabularnewline
0.37 & 408.692472634944 & 7.81423150204535 \tabularnewline
0.38 & 410.039951120896 & 7.46987309167804 \tabularnewline
0.39 & 411.331250056976 & 7.23117721981285 \tabularnewline
0.4 & 412.583777472176 & 7.10735667092814 \tabularnewline
0.41 & 413.815450356754 & 7.09913972063555 \tabularnewline
0.42 & 415.043527982825 & 7.19814143477923 \tabularnewline
0.43 & 416.283575287336 & 7.38746701697 \tabularnewline
0.44 & 417.548641445791 & 7.64382438323201 \tabularnewline
0.45 & 418.84872427558 & 7.94237127691744 \tabularnewline
0.46 & 420.190563169376 & 8.25912420772818 \tabularnewline
0.47 & 421.57776419109 & 8.5729620100899 \tabularnewline
0.48 & 423.011216539098 & 8.86810044642123 \tabularnewline
0.49 & 424.489717908476 & 9.13548223610172 \tabularnewline
0.5 & 426.010696008193 & 9.37094831390365 \tabularnewline
0.51 & 427.570901675334 & 9.57666521659115 \tabularnewline
0.52 & 429.166959303823 & 9.75773638577022 \tabularnewline
0.53 & 430.795691755386 & 9.92031451274067 \tabularnewline
0.54 & 432.454184074930 & 10.0687896915301 \tabularnewline
0.55 & 434.139604281757 & 10.2052496700981 \tabularnewline
0.56 & 435.848849878637 & 10.3264893388633 \tabularnewline
0.57 & 437.578125978606 & 10.4252763471060 \tabularnewline
0.58 & 439.322578409305 & 10.4911493615779 \tabularnewline
0.59 & 441.076100177818 & 10.5125768025280 \tabularnewline
0.6 & 442.83140380005 & 10.4798757235208 \tabularnewline
0.61 & 444.58041008168 & 10.3855025117221 \tabularnewline
0.62 & 446.314952751254 & 10.2289319472962 \tabularnewline
0.63 & 448.027745107933 & 10.0156459896998 \tabularnewline
0.64 & 449.713506211354 & 9.75939105853806 \tabularnewline
0.65 & 451.370105847618 & 9.48130411459812 \tabularnewline
0.66 & 452.999564540244 & 9.20928015849035 \tabularnewline
0.67 & 454.608741711983 & 8.97640750954777 \tabularnewline
0.68 & 456.209565479277 & 8.81847042184049 \tabularnewline
0.69 & 457.818703434151 & 8.7670271731395 \tabularnewline
0.7 & 459.456643549767 & 8.84699094476024 \tabularnewline
0.71 & 461.146241035129 & 9.06896312271629 \tabularnewline
0.72 & 462.910877234439 & 9.42705730804327 \tabularnewline
0.73 & 464.77245198575 & 9.89927077380976 \tabularnewline
0.74 & 466.749471245767 & 10.4519240243500 \tabularnewline
0.75 & 468.855481857991 & 11.0430111824078 \tabularnewline
0.76 & 471.098040982514 & 11.6311000592799 \tabularnewline
0.77 & 473.478300919432 & 12.1774905188954 \tabularnewline
0.78 & 475.991169113332 & 12.6514921314529 \tabularnewline
0.79 & 478.625906234069 & 13.0294346277291 \tabularnewline
0.8 & 481.366988080066 & 13.2951826356831 \tabularnewline
0.81 & 484.195097412696 & 13.4381457257573 \tabularnewline
0.82 & 487.088216864342 & 13.4506612067782 \tabularnewline
0.83 & 490.022916855707 & 13.3279540938580 \tabularnewline
0.84 & 492.976002678029 & 13.0701671961552 \tabularnewline
0.85 & 495.926634517144 & 12.6859607803199 \tabularnewline
0.86 & 498.858833880551 & 12.1969489542557 \tabularnewline
0.87 & 501.763985493437 & 11.6398030143079 \tabularnewline
0.88 & 504.642675121364 & 11.0640725492933 \tabularnewline
0.89 & 507.505179763288 & 10.5217369380242 \tabularnewline
0.9 & 510.370327393517 & 10.0522921324418 \tabularnewline
0.91 & 513.263244855856 & 9.66689834304157 \tabularnewline
0.92 & 516.213297454099 & 9.34391521394727 \tabularnewline
0.93 & 519.253438647267 & 9.04649025258257 \tabularnewline
0.94 & 522.420213895895 & 8.75294136957157 \tabularnewline
0.95 & 525.749207766871 & 8.4688760098436 \tabularnewline
0.96 & 529.254535555018 & 8.18114065461974 \tabularnewline
0.97 & 532.877281114261 & 7.7992522905667 \tabularnewline
0.98 & 536.399372391948 & 7.23844630046968 \tabularnewline
0.99 & 539.370568640775 & 6.648348786937 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48819&T=1

[TABLE]
[ROW][C]Harrell-Davis Quantiles[/C][/ROW]
[ROW][C]quantiles[/C][C]value[/C][C]standard error[/C][/ROW]
[ROW][C]0.01[/C][C]310.618048158856[/C][C]20.9581601859364[/C][/ROW]
[ROW][C]0.02[/C][C]318.191997403201[/C][C]17.0253393910196[/C][/ROW]
[ROW][C]0.03[/C][C]325.891635320383[/C][C]13.6066050711331[/C][/ROW]
[ROW][C]0.04[/C][C]332.532019378215[/C][C]11.2951840456643[/C][/ROW]
[ROW][C]0.05[/C][C]337.896160855896[/C][C]9.97562348311745[/C][/ROW]
[ROW][C]0.06[/C][C]342.234983451647[/C][C]9.33890971330733[/C][/ROW]
[ROW][C]0.07[/C][C]345.887719644357[/C][C]9.14769532201808[/C][/ROW]
[ROW][C]0.08[/C][C]349.124009143959[/C][C]9.24048831369394[/C][/ROW]
[ROW][C]0.09[/C][C]352.117585483879[/C][C]9.48191109637058[/C][/ROW]
[ROW][C]0.1[/C][C]354.964863989608[/C][C]9.74730787988732[/C][/ROW]
[ROW][C]0.11[/C][C]357.708728178848[/C][C]9.93094690446412[/C][/ROW]
[ROW][C]0.12[/C][C]360.357844425304[/C][C]9.96351749927225[/C][/ROW]
[ROW][C]0.13[/C][C]362.901934140727[/C][C]9.81971693219385[/C][/ROW]
[ROW][C]0.14[/C][C]365.324259116182[/C][C]9.51999444690247[/C][/ROW]
[ROW][C]0.15[/C][C]367.611398047521[/C][C]9.12167677581195[/C][/ROW]
[ROW][C]0.16[/C][C]369.759780094626[/C][C]8.7046004148612[/C][/ROW]
[ROW][C]0.17[/C][C]371.778625189412[/C][C]8.35480009387524[/C][/ROW]
[ROW][C]0.18[/C][C]373.689501762001[/C][C]8.14642309151032[/C][/ROW]
[ROW][C]0.19[/C][C]375.523257073979[/C][C]8.12690722613955[/C][/ROW]
[ROW][C]0.2[/C][C]377.315393624093[/C][C]8.30683766693104[/C][/ROW]
[ROW][C]0.21[/C][C]379.101011072459[/C][C]8.66139592438748[/C][/ROW]
[ROW][C]0.22[/C][C]380.910261360528[/C][C]9.1402747963431[/C][/ROW]
[ROW][C]0.23[/C][C]382.764969223780[/C][C]9.67961847403066[/C][/ROW]
[ROW][C]0.24[/C][C]384.67674169597[/C][C]10.2164305136047[/C][/ROW]
[ROW][C]0.25[/C][C]386.646594446921[/C][C]10.6923788037559[/C][/ROW]
[ROW][C]0.26[/C][C]388.66589723474[/C][C]11.0625764847387[/C][/ROW]
[ROW][C]0.27[/C][C]390.718299323406[/C][C]11.2949383793117[/C][/ROW]
[ROW][C]0.28[/C][C]392.782236259509[/C][C]11.3750443069269[/C][/ROW]
[ROW][C]0.29[/C][C]394.833629543453[/C][C]11.2995684941529[/C][/ROW]
[ROW][C]0.3[/C][C]396.84845188785[/C][C]11.0809417879458[/C][/ROW]
[ROW][C]0.31[/C][C]398.804921321466[/C][C]10.7390065178731[/C][/ROW]
[ROW][C]0.32[/C][C]400.685185986214[/C][C]10.3014620668767[/C][/ROW]
[ROW][C]0.33[/C][C]402.476450234037[/C][C]9.80013816241935[/C][/ROW]
[ROW][C]0.34[/C][C]404.171559891771[/C][C]9.26825217292529[/C][/ROW]
[ROW][C]0.35[/C][C]405.769106037501[/C][C]8.73960401156921[/C][/ROW]
[ROW][C]0.36[/C][C]407.273124798386[/C][C]8.24508007653534[/C][/ROW]
[ROW][C]0.37[/C][C]408.692472634944[/C][C]7.81423150204535[/C][/ROW]
[ROW][C]0.38[/C][C]410.039951120896[/C][C]7.46987309167804[/C][/ROW]
[ROW][C]0.39[/C][C]411.331250056976[/C][C]7.23117721981285[/C][/ROW]
[ROW][C]0.4[/C][C]412.583777472176[/C][C]7.10735667092814[/C][/ROW]
[ROW][C]0.41[/C][C]413.815450356754[/C][C]7.09913972063555[/C][/ROW]
[ROW][C]0.42[/C][C]415.043527982825[/C][C]7.19814143477923[/C][/ROW]
[ROW][C]0.43[/C][C]416.283575287336[/C][C]7.38746701697[/C][/ROW]
[ROW][C]0.44[/C][C]417.548641445791[/C][C]7.64382438323201[/C][/ROW]
[ROW][C]0.45[/C][C]418.84872427558[/C][C]7.94237127691744[/C][/ROW]
[ROW][C]0.46[/C][C]420.190563169376[/C][C]8.25912420772818[/C][/ROW]
[ROW][C]0.47[/C][C]421.57776419109[/C][C]8.5729620100899[/C][/ROW]
[ROW][C]0.48[/C][C]423.011216539098[/C][C]8.86810044642123[/C][/ROW]
[ROW][C]0.49[/C][C]424.489717908476[/C][C]9.13548223610172[/C][/ROW]
[ROW][C]0.5[/C][C]426.010696008193[/C][C]9.37094831390365[/C][/ROW]
[ROW][C]0.51[/C][C]427.570901675334[/C][C]9.57666521659115[/C][/ROW]
[ROW][C]0.52[/C][C]429.166959303823[/C][C]9.75773638577022[/C][/ROW]
[ROW][C]0.53[/C][C]430.795691755386[/C][C]9.92031451274067[/C][/ROW]
[ROW][C]0.54[/C][C]432.454184074930[/C][C]10.0687896915301[/C][/ROW]
[ROW][C]0.55[/C][C]434.139604281757[/C][C]10.2052496700981[/C][/ROW]
[ROW][C]0.56[/C][C]435.848849878637[/C][C]10.3264893388633[/C][/ROW]
[ROW][C]0.57[/C][C]437.578125978606[/C][C]10.4252763471060[/C][/ROW]
[ROW][C]0.58[/C][C]439.322578409305[/C][C]10.4911493615779[/C][/ROW]
[ROW][C]0.59[/C][C]441.076100177818[/C][C]10.5125768025280[/C][/ROW]
[ROW][C]0.6[/C][C]442.83140380005[/C][C]10.4798757235208[/C][/ROW]
[ROW][C]0.61[/C][C]444.58041008168[/C][C]10.3855025117221[/C][/ROW]
[ROW][C]0.62[/C][C]446.314952751254[/C][C]10.2289319472962[/C][/ROW]
[ROW][C]0.63[/C][C]448.027745107933[/C][C]10.0156459896998[/C][/ROW]
[ROW][C]0.64[/C][C]449.713506211354[/C][C]9.75939105853806[/C][/ROW]
[ROW][C]0.65[/C][C]451.370105847618[/C][C]9.48130411459812[/C][/ROW]
[ROW][C]0.66[/C][C]452.999564540244[/C][C]9.20928015849035[/C][/ROW]
[ROW][C]0.67[/C][C]454.608741711983[/C][C]8.97640750954777[/C][/ROW]
[ROW][C]0.68[/C][C]456.209565479277[/C][C]8.81847042184049[/C][/ROW]
[ROW][C]0.69[/C][C]457.818703434151[/C][C]8.7670271731395[/C][/ROW]
[ROW][C]0.7[/C][C]459.456643549767[/C][C]8.84699094476024[/C][/ROW]
[ROW][C]0.71[/C][C]461.146241035129[/C][C]9.06896312271629[/C][/ROW]
[ROW][C]0.72[/C][C]462.910877234439[/C][C]9.42705730804327[/C][/ROW]
[ROW][C]0.73[/C][C]464.77245198575[/C][C]9.89927077380976[/C][/ROW]
[ROW][C]0.74[/C][C]466.749471245767[/C][C]10.4519240243500[/C][/ROW]
[ROW][C]0.75[/C][C]468.855481857991[/C][C]11.0430111824078[/C][/ROW]
[ROW][C]0.76[/C][C]471.098040982514[/C][C]11.6311000592799[/C][/ROW]
[ROW][C]0.77[/C][C]473.478300919432[/C][C]12.1774905188954[/C][/ROW]
[ROW][C]0.78[/C][C]475.991169113332[/C][C]12.6514921314529[/C][/ROW]
[ROW][C]0.79[/C][C]478.625906234069[/C][C]13.0294346277291[/C][/ROW]
[ROW][C]0.8[/C][C]481.366988080066[/C][C]13.2951826356831[/C][/ROW]
[ROW][C]0.81[/C][C]484.195097412696[/C][C]13.4381457257573[/C][/ROW]
[ROW][C]0.82[/C][C]487.088216864342[/C][C]13.4506612067782[/C][/ROW]
[ROW][C]0.83[/C][C]490.022916855707[/C][C]13.3279540938580[/C][/ROW]
[ROW][C]0.84[/C][C]492.976002678029[/C][C]13.0701671961552[/C][/ROW]
[ROW][C]0.85[/C][C]495.926634517144[/C][C]12.6859607803199[/C][/ROW]
[ROW][C]0.86[/C][C]498.858833880551[/C][C]12.1969489542557[/C][/ROW]
[ROW][C]0.87[/C][C]501.763985493437[/C][C]11.6398030143079[/C][/ROW]
[ROW][C]0.88[/C][C]504.642675121364[/C][C]11.0640725492933[/C][/ROW]
[ROW][C]0.89[/C][C]507.505179763288[/C][C]10.5217369380242[/C][/ROW]
[ROW][C]0.9[/C][C]510.370327393517[/C][C]10.0522921324418[/C][/ROW]
[ROW][C]0.91[/C][C]513.263244855856[/C][C]9.66689834304157[/C][/ROW]
[ROW][C]0.92[/C][C]516.213297454099[/C][C]9.34391521394727[/C][/ROW]
[ROW][C]0.93[/C][C]519.253438647267[/C][C]9.04649025258257[/C][/ROW]
[ROW][C]0.94[/C][C]522.420213895895[/C][C]8.75294136957157[/C][/ROW]
[ROW][C]0.95[/C][C]525.749207766871[/C][C]8.4688760098436[/C][/ROW]
[ROW][C]0.96[/C][C]529.254535555018[/C][C]8.18114065461974[/C][/ROW]
[ROW][C]0.97[/C][C]532.877281114261[/C][C]7.7992522905667[/C][/ROW]
[ROW][C]0.98[/C][C]536.399372391948[/C][C]7.23844630046968[/C][/ROW]
[ROW][C]0.99[/C][C]539.370568640775[/C][C]6.648348786937[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=48819&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48819&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Harrell-Davis Quantiles
quantilesvaluestandard error
0.01310.61804815885620.9581601859364
0.02318.19199740320117.0253393910196
0.03325.89163532038313.6066050711331
0.04332.53201937821511.2951840456643
0.05337.8961608558969.97562348311745
0.06342.2349834516479.33890971330733
0.07345.8877196443579.14769532201808
0.08349.1240091439599.24048831369394
0.09352.1175854838799.48191109637058
0.1354.9648639896089.74730787988732
0.11357.7087281788489.93094690446412
0.12360.3578444253049.96351749927225
0.13362.9019341407279.81971693219385
0.14365.3242591161829.51999444690247
0.15367.6113980475219.12167677581195
0.16369.7597800946268.7046004148612
0.17371.7786251894128.35480009387524
0.18373.6895017620018.14642309151032
0.19375.5232570739798.12690722613955
0.2377.3153936240938.30683766693104
0.21379.1010110724598.66139592438748
0.22380.9102613605289.1402747963431
0.23382.7649692237809.67961847403066
0.24384.6767416959710.2164305136047
0.25386.64659444692110.6923788037559
0.26388.6658972347411.0625764847387
0.27390.71829932340611.2949383793117
0.28392.78223625950911.3750443069269
0.29394.83362954345311.2995684941529
0.3396.8484518878511.0809417879458
0.31398.80492132146610.7390065178731
0.32400.68518598621410.3014620668767
0.33402.4764502340379.80013816241935
0.34404.1715598917719.26825217292529
0.35405.7691060375018.73960401156921
0.36407.2731247983868.24508007653534
0.37408.6924726349447.81423150204535
0.38410.0399511208967.46987309167804
0.39411.3312500569767.23117721981285
0.4412.5837774721767.10735667092814
0.41413.8154503567547.09913972063555
0.42415.0435279828257.19814143477923
0.43416.2835752873367.38746701697
0.44417.5486414457917.64382438323201
0.45418.848724275587.94237127691744
0.46420.1905631693768.25912420772818
0.47421.577764191098.5729620100899
0.48423.0112165390988.86810044642123
0.49424.4897179084769.13548223610172
0.5426.0106960081939.37094831390365
0.51427.5709016753349.57666521659115
0.52429.1669593038239.75773638577022
0.53430.7956917553869.92031451274067
0.54432.45418407493010.0687896915301
0.55434.13960428175710.2052496700981
0.56435.84884987863710.3264893388633
0.57437.57812597860610.4252763471060
0.58439.32257840930510.4911493615779
0.59441.07610017781810.5125768025280
0.6442.8314038000510.4798757235208
0.61444.5804100816810.3855025117221
0.62446.31495275125410.2289319472962
0.63448.02774510793310.0156459896998
0.64449.7135062113549.75939105853806
0.65451.3701058476189.48130411459812
0.66452.9995645402449.20928015849035
0.67454.6087417119838.97640750954777
0.68456.2095654792778.81847042184049
0.69457.8187034341518.7670271731395
0.7459.4566435497678.84699094476024
0.71461.1462410351299.06896312271629
0.72462.9108772344399.42705730804327
0.73464.772451985759.89927077380976
0.74466.74947124576710.4519240243500
0.75468.85548185799111.0430111824078
0.76471.09804098251411.6311000592799
0.77473.47830091943212.1774905188954
0.78475.99116911333212.6514921314529
0.79478.62590623406913.0294346277291
0.8481.36698808006613.2951826356831
0.81484.19509741269613.4381457257573
0.82487.08821686434213.4506612067782
0.83490.02291685570713.3279540938580
0.84492.97600267802913.0701671961552
0.85495.92663451714412.6859607803199
0.86498.85883388055112.1969489542557
0.87501.76398549343711.6398030143079
0.88504.64267512136411.0640725492933
0.89507.50517976328810.5217369380242
0.9510.37032739351710.0522921324418
0.91513.2632448558569.66689834304157
0.92516.2132974540999.34391521394727
0.93519.2534386472679.04649025258257
0.94522.4202138958958.75294136957157
0.95525.7492077668718.4688760098436
0.96529.2545355550188.18114065461974
0.97532.8772811142617.7992522905667
0.98536.3993723919487.23844630046968
0.99539.3705686407756.648348786937


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
library(Hmisc)
myseq <- seq(par1, par2, par3)
hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE)
bitmap(file='test1.png')
plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'quantiles',header=TRUE)
a<-table.element(a,'value',header=TRUE)
a<-table.element(a,'standard error',header=TRUE)
a<-table.row.end(a)
length(hd)
for (i in 1:length(hd))
{
a<-table.row.start(a)
a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE)
a<-table.element(a,as.matrix(hd[i])[1,1])
a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')